Automated microscope platform with improved imaging and accurate neuron reconstruction capabilities for high-throughput studies of neuroregeneration

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Project Summary/Abstract The mammalian central nervous system typically fails to regenerate after injury, leading to incurable conditions with immense healthcare burdens. An exception is a remarkable effect called lesion conditioning, where injury to a neuron’s peripheral fiber activates cellular processes to greatly enhance neuroregeneration. Exploiting this “conditioned” form of regeneration for therapy requires a clear understanding of its underlying mechanisms, which is still lacking despite intense research in mammalian systems. Specifically, there is a knowledge gap regarding the impact of neuron type, morphology, and connectivity on regeneration. An in vivo approach in the worm C. elegans can reveal the cellular mechanisms underlying conditioned regeneration by femtosecond laser surgery and high-precision microscopy of single neuronal fibers. Three genes identified in the worm also modulate mammalian lesion conditioning, demonstrating that this approach can discover key conserved mechanisms. Even though this approach is effective at examining single genes or mechanisms, its manual execution precludes it from defining regenerative capacity across multiple neuron types and surgery locations. Thus, there is a critical need to accelerate imaging and laser surgery to comprehensively study regeneration. The overall objectives of the proposed project are to optimize an automated microscope platform and validate it by broadly testing many neuron types in C. elegans for conditioned regeneration. The rationale for this project is that an automated platform will permit large-scale regeneration studies that are currently impractical but required to fully map regenerative pathways. The objectives will be achieved by the following Specific Aims: 1) Improve image contrast to permit computer visualization of neurites. 2) Develop a real-time machine learning approach for automated neuron reconstruction. 3) Assess regenerative capacity in a broad range of neuron types in C. elegans. Work for Aim 1 will control the sample illumination and apply novel, real-time image processing to improve the contrast between neurons and their background. In Aim 2, these improved images will be reversibly compressed, computationally enhanced, reconstructed into a neuron model, and annotated for surgery. In Aim 3, the integrated platform will be used to perform surgery and reimage neurites in many neuron types in C. elegans to examine the role of key genes in regeneration. Innovative aspects of the proposed project include: an invertebrate model for lesion conditioning, new optical methods for improving imaging contrast, and novel machine learning techniques for real-time neuronal reconstruction. The expected outcomes of the proposed study are deep insights into the fundamental genetic and cellular mechanisms that determine the ability to execute conditioned regeneration and the validation of an automated microscope platform for high throughput imaging and surgery. These results are significant because they will establish important drivers of regeneration in the central nervous system, including potential therapeutic targets that could effectively treat currently incurable injuries and diseases of the nervous system.